The invention discloses a traffic flow prediction method and system based on a selective attention mechanism, and belongs to the field of intelligent traffic and machine learning. The traffic flow prediction method and system based on the selective attention mechanism comprises the following steps: firstly, acquiring historical traffic data, road topology data and road attribute data; then, based on a KGCN-GSAM model, according to the road topology data and the road attribute data, establishing a traffic prediction model; and then, based on the obtained traffic prediction model, according to historical traffic data, prediction of a traffic prediction value in a next time period is carried out. By using the KGCN-GSAM model for traffic prediction, the accuracy of traffic prediction is effectively improved.
本发明公开了一种基于选择注意力机制的交通流量预测方法及系统,属于智能交通和机器学习领域。该基于选择注意力机制的交通流量预测方法及系统包括:首先,获取历史交通数据、道路拓扑数据和道路属性数据;接着,基于KGCN‑GSAM模型,根据道路拓扑数据和道路属性数据,建立交通预测模型;然后,基于所得交通预测模型,根据历史交通数据,进行下一时段内的交通预测值的预测。通过运用KGCN‑GSAM模型交通预测,本发明有效提高了交通预测的精准度。
Traffic flow prediction method and system based on selective attention mechanism
一种基于选择注意力机制的交通流量预测方法及系统
07.06.2024
Patent
Elektronische Ressource
Chinesisch
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